1. Technical Field
Embodiments of the subject matter disclosed herein generally relate to methods and apparatuses for processing seismic data, more particularly, to adaptive rank reduction methods for attenuating (subtracting) the noise in recorded seismic data.
2. Discussion of the Background
During the past years, the interest in developing new oil and gas production fields on land and offshore has continued to increase. Therefore, geophysical surveys have become more sophisticated in order to more accurately decide where to drill to avoid a dry well. The term “geophysical survey” refers to a systematic collection of geophysical data using various techniques. The data may be collected from above, on or below the Earth's surface and the sea surface. Seismic methods (such as reflection seismology and seismic tomography) are the most frequently used techniques in geophysical surveys due to their efficiency in terms of penetration depth, relatively reduced cost and low environmental impact.
A seismic survey involves deploying one or more seismic sources and seismic detectors at predetermined locations. The seismic sources generate pressure (seismic) waves, which propagate into the geological formations. A seismic source generating a seismic wave is known as a “shot.” Changes in acoustic properties of the geological formation scatter the seismic waves, changing their direction of propagation and other properties. Part of the energy emitted by the seismic sources is reflected inside the geological formation and reaches the seismic detectors to produce seismic data.
In a land data acquisition system, the detectors may be arranged along receiver lines, while the seismic sources are usually positioned at shot points in-between the receiver lines on shot lines parallel to the receiver lines as the land topography allows.
The recorded seismic data corresponds to signals (due to seismic wave reflections inside the geological formation) and to overlapping noise. The seismic data includes values proportional to pressure versus time or to displacement versus time as sensed by seismic detectors (e.g., hydrophones and geophones), associated with the corresponding positions of the detectors and of the shot point.
The seismic data processing yields a profile (image) of the geophysical structure (subsurface). While this profile does not provide an accurate location for the oil and gas reservoirs, it suggests, to those trained in the field, the presence or absence of oil and/or gas reservoirs.
The seismic data may suffer from high levels of noise, making the task of processing and interpreting the data difficult. The noise may be random (i.e., uncorrelated with the shot) or coherent (i.e., correlated with the shot or the detector). The removal (attenuation) of random noise normally relies on the fact that random noise is not predictable (e.g., non-orthogonal) relative to the shot. When the data is altered (e.g., for removing the noise), it is desirable to preserve the amplitude versus offset (AVO) behavior of the signal in order to obtain reliable subsurface information. In other words, since seismic data from plural detectors at various locations is assembled to generate an image of the subsurface, the manner in which corrections (such as noise removal) affect the data is desirable to be the same in terms of detector locations and shots. Land seismic data is often overwhelmed by coherent noise, which, if not removed, renders the extracted information unreliable.
The most common kind of coherent noise in land seismic data is the ground roll (or Rayleigh wave). Other types of coherent noise include air blast, flexure waves and near-surface reverberations. While the ground roll has very low frequency and velocity compared to reflection data, some noise types such as air blast or near-surface reverberations have a broader bandwidth (i.e., range of frequencies) and may have a higher velocity than the ground roll. In typical land acquisition geometries (i.e., arrangements of the seismic source(s) and the detectors), the noise is aliased spatially due to sparse geometries. The spatial and temporal variations of phase velocity versus frequency and the high amplitude variations of noise lead to a poor signal to noise ratio.
Some methods for removing noise (i.e., for noise attenuation) from seismic data use the velocity and frequency information to separate the noise and from the signal. While some methods can deal with aliased noise, approaches that in addition have the ability to deal with variable noise conditions are necessary.
When methods (such as, frequency and wave number—FK—fan filters) based on the assumption of regular detector spacing are used, smear artifacts occur in the subsurface image. Other methods (such as frequency and distance from the source—FX—fan filters) that are adaptive locally are effective in removing the orthogonal coherent noise and are able to handle irregular geometry, but are unable to adequately attenuate aliased noise. Recently have been developed methods that perform coherent noise attenuation based on an FX domain rank reduction. These methods provide the advantages of an FX filter and obtain a coherent noise model (including aliased noise), under the assumption that coherent noise is much stronger than the signal and that the coherent noise is orthogonal to the signal. However, in fact, the signal and the coherent noise are not orthogonal.
Accordingly, it would be desirable to provide rank reduction methods capable to separate strong non-orthogonal coherent noise from signal in land seismic data better than the conventional methods.